Recent methods generalize convolutional layers from Euclidean domains to graph-structured data by approximating the eigenbasis of the graph Laplacian. The computationally-efficient and broadly-used ...

1 Department of Computer Science and Engineering, Kishoreganj University, Kishoreganj, Bangladesh. 2 Department of Electrical and Computer Engineering, North South University, Dhaka, Bangladesh. 3 ...

Department of Chemistry and Research Institute for Natural Science, Korea University, Seoul 02841, Korea ...

The dual-channel graph convolutional neural networks based on hybrid features jointly model the different features of networks, so that the features can learn each other and improve the performance of ...

Abstract: In recent years, active learning (AL) methods have provided a feasible approach to alleviate the problem of limited labeled samples in deep learning projects. Existing AL algorithms ...

With the rapid development of power grid infrastructure, especially the increasing number of ultra-high voltage (UHV) projects, knowledge extracted from historical engineering data is collected and ...

the main.py can be run from the command line interface with the following commands, where -f (dataset file) and -r (the number of parid replicates) are the two required parameters. An example command ...

Abstract: Cancer driver genes are mutated genes that play a key role in the growth of cancer cells. Accurately identifying the cancer driver genes helps us understand cancer’s pathogenesis and develop ...